Driven by initiatives such as the Human Genome, 1000 Genomes, ENCODE, and GTEx Projects, genetics and genomics have taken a central role in the biomedical sciences. In the same way, advances in computation are driving the mathematical sciences forward. These factors, the increasingly quantitative nature of biomedical research, and the explosive growth of genomic data have resulted in an increasing demand for individuals trained at the interface of genomics and the mathematical sciences. Recognizing this demand, the NHGRI and NIGMS in 2008 convened a workshop focused on Research Training Needs in Statistical Genetics and Genetic Epidemiology. Participants affirmed the existence of a key need, stating there is not a sufficiently trained cadre of scientists to develop methods and analyze the vast amount of data generated from population genomics studies employing current and rapidly emerging technologies. In the intervening years, the increasing volume and variety of genomic data has made this need even more acute. In a series of workshops in 2012 and 2013, NHGRI advisors reaffirmed this training need, and advocated maintaining investment in genomics sciences training while expanding the statistical and informatics component. The emerging focus on big data in research in general and biomedical research in particular is expanding this need further. The continuing goal of the University of Michigan Genome Science Training Program (GSTP) is to fill this need by training predoctoral and postdoctoral trainees at the interface of genetics, genomics, and the mathematical sciences, with particular emphasis on training statistical human geneticists, genetic epidemiologists, bioinformaticians, and human molecular geneticists with a strong grounding in statistics and computation. The GSTP is based in the participating departments of Biostatistics, Human Genetics, and Epidemiology, and now also the graduate program in Bioinformatics, with other participating faculty in Ecology and Evolutionary Biology; Environmental Health Sciences; Molecular, Cellular, and Developmental Biology; and Statistics. The fundamental premise of the GSTP is that graduates should have substantial training in the mathematical and biological sciences and at their interface. Such training facilitates communication between disciplines, identification of important problems, and of the statistical and computational tools required to solve those problems. We request support for ten predoctoral trainees and three postdoctoral trainees, consistent with the last five years o the GSTP. Trainees will be supported for two to three years to provide time for the interdisciplinary training we have demonstrated is critical to their success. Graduates of the GSTP will continue to help fill the need for quantitative genome scientists, and in so doing, help the NHGRI achieve its goals of translation of genomic information into advances in our understanding of human health and disease.